Privacy level evaluation of differential privacy for time series based on filtering theory
The current differential privacy preserving methods on correlated time series were not designed by protecting against a specific attack model,and the privacy level of them couldn’t be measured.Therefore,an attack model was put forward to solve the above problems.Since the noise series added by these...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2017-05-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017110/ |
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| author | Wen-jun XIONG Zheng-quan XU Hao WANG |
| author_facet | Wen-jun XIONG Zheng-quan XU Hao WANG |
| author_sort | Wen-jun XIONG |
| collection | DOAJ |
| description | The current differential privacy preserving methods on correlated time series were not designed by protecting against a specific attack model,and the privacy level of them couldn’t be measured.Therefore,an attack model was put forward to solve the above problems.Since the noise series added by these methods was independent and identically distributed,and the time series could be seen as a short-time stationary process,a linear filter was designed based on filtering theory,in order to filter out the noise series.Experimental results show that the proposed attack model is valid,and can work as a unified measurement for these methods. |
| format | Article |
| id | doaj-art-76a4275f4d8340058e382179d0fc2e08 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2017-05-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-76a4275f4d8340058e382179d0fc2e082025-01-14T07:12:27ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2017-05-013817218159710498Privacy level evaluation of differential privacy for time series based on filtering theoryWen-jun XIONGZheng-quan XUHao WANGThe current differential privacy preserving methods on correlated time series were not designed by protecting against a specific attack model,and the privacy level of them couldn’t be measured.Therefore,an attack model was put forward to solve the above problems.Since the noise series added by these methods was independent and identically distributed,and the time series could be seen as a short-time stationary process,a linear filter was designed based on filtering theory,in order to filter out the noise series.Experimental results show that the proposed attack model is valid,and can work as a unified measurement for these methods.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017110/differential privacyprivacy preservingcorrelated time seriesattack model |
| spellingShingle | Wen-jun XIONG Zheng-quan XU Hao WANG Privacy level evaluation of differential privacy for time series based on filtering theory Tongxin xuebao differential privacy privacy preserving correlated time series attack model |
| title | Privacy level evaluation of differential privacy for time series based on filtering theory |
| title_full | Privacy level evaluation of differential privacy for time series based on filtering theory |
| title_fullStr | Privacy level evaluation of differential privacy for time series based on filtering theory |
| title_full_unstemmed | Privacy level evaluation of differential privacy for time series based on filtering theory |
| title_short | Privacy level evaluation of differential privacy for time series based on filtering theory |
| title_sort | privacy level evaluation of differential privacy for time series based on filtering theory |
| topic | differential privacy privacy preserving correlated time series attack model |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017110/ |
| work_keys_str_mv | AT wenjunxiong privacylevelevaluationofdifferentialprivacyfortimeseriesbasedonfilteringtheory AT zhengquanxu privacylevelevaluationofdifferentialprivacyfortimeseriesbasedonfilteringtheory AT haowang privacylevelevaluationofdifferentialprivacyfortimeseriesbasedonfilteringtheory |